PT-2026-40126

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from pretrained method uses torch.load to load the pytorch model.bin weight file without enabling the security-restrictive...

CVE-2026-31239

The CVE-2026-31239 entry concerns the Mamba language model framework up to version 2.2.6. The issue is insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file...

GHSA-J7W6-VPVQ-J3GM Diffusers has a `trust_remote_code` bypass via `custom_pipeline` and local custom components

Background This vulnerability is found in the DiffusionPipeline.frompretrained flow, which is used to load a pipeline from the HuggingFace Hub. This function accepts an optional custompipeline keyword argument: the name of a Python file in the repo that contains a custom class inheriting from...

Diffusers has a `trust_remote_code` bypass via `custom_pipeline` and local custom components

Background This vulnerability is found in the DiffusionPipeline.frompretrained flow, which is used to load a pipeline from the HuggingFace Hub. This function accepts an optional custompipeline keyword argument: the name of a Python file in the repo that contains a custom class inheriting from...

PT-2026-39298

Name of the Vulnerable Software and Affected Versions Diffusers versions prior to 0.38.0 Description An issue exists in the DiffusionPipeline.from pretrained flow when loading pipelines from Hugging Face Hub repositories. The resolve custom pipeline and cls function in pipeline loading utils.py...

GLiNER Guard: Unified Encoder Family for Production LLM Safety and Privacy

Production LLM systems require both safety moderation and PII detection under strict latency and cost constraints. This creates a trade-off: autoregressive moderators are accurate but expensive, while lightweight encoders are faster but less capable. We present GLiNER Guard GLiGuard, a unified...

SGLang has an Improper Input Validation/Injection Issue

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation results in deserialization. The attack can be executed remotely. A hi...

Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')

Overview sglang is a SGLang is a fast serving framework for large language models and vision language models. Affected versions of this package are vulnerable to Improper Neutralization of Special Elements in Output Used by a Downstream Component 'Injection' via the gettokenizer function in the...

CVE-2026-7669

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation of the argument trustremotecode with the input False as part of Boole...

CVE-2026-7669

Affected software: sgl-project SGLang (up to 0.5.9). The vulnerability targets the function get_tokenizer in python/sglang/srt/utils/hf_transformers_utils.py within the HuggingFace Transformer Handler. Root cause is deserialization triggered by input manipulation. Impact is remote execution with ...

EUVD-2026-26802

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation results in deserialization. The attack can be executed remotely. A hi...

CVE-2026-7669 sgl-project SGLang HuggingFace Transformer hf_transformers_utils.py get_tokenizer code injection

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation of the argument trustremotecode with the input False as part of Boole...

PT-2026-36639

Name of the Vulnerable Software and Affected Versions sgl-project SGLang versions prior to 0.6.0 Description A code injection issue exists in the HuggingFace Transformer Handler within the get tokenizer function of the python/sglang/srt/utils/hf transformers utils.py file. When a caller sets the...

fl-manager-components-datasets-torch (=0.1.0), fl-manager-components-formatters-pillow (=0.1.0) +11 more potentially affected by CVE-2026-24178 via nvflare (>=2.2.0 <=2.7.1)

nvflare PYPI version =2.2.0, =0.1.0, =0.2.0, =3.1.27, =3.1.27, =3.1.29, =3.1.31 Source cves: CVE-2026-24178 Source advisory: SNYK:PYTHON-NVFLARE-16318747...

GHSA-RXPQ-XGQX-FR7P InstructLab Includes Functionality from Untrusted Control Sphere

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

EUVD-2026-24752

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

InstructLab Includes Functionality from Untrusted Control Sphere

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

Inclusion of Functionality from Untrusted Control Sphere

Overview instructlab is a Core package for interacting with InstructLab Affected versions of this package are vulnerable to Inclusion of Functionality from Untrusted Control Sphere via default trustremotecode=True for loading models from HuggingFacein in linuxtrain.py file. An attacker can execut...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...